Name
Abstract | ||
|---|---|---|
A novel robust least squares constant modulus algorithm (LSCMA) is proposed for blind adaptive beamforming, which is based on explicit modeling of uncertainty in the desired signal array. To improve robustness, the weight vector is optimized to involve minimization of cost function, while imposing the oblique projection constraint on the weight vector and maintaining a distortionless response for the worst-case signal steering vector. The proposed algorithm appears to be an appealing technique for blind adaptive beamforming that combines excellent robustness with low computational complexity. The numerical experiments have been carried out to demonstrate the superiority of the proposed algorithm on beampattern control and output SINR enhancement. © 2011 IEEE. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISCIT.2011.6092166 | ISCIT |
Keywords | Field | DocType |
adaptive beamforming,least squares constant modulus algorithm (lscma),signal steering vector mismatches,taylor-series expansion,blind source separation,robustness,vectors,least square,signal processing,signal to noise ratio,interference,computational complexity,oblique projection,cost function,taylor series expansion | Least squares,Oblique projection,Adaptive beamformer,Control theory,Computer science,Signal-to-noise ratio,Weight,Robustness (computer science),Blind signal separation,Computational complexity theory | Conference |
Volume | Issue | ISSN |
null | null | null |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Song | 1 | 15 | 15.82 |
| Jinkuan Wang | 2 | 0 | 0.34 |
| Qiuming Li | 3 | 0 | 1.35 |
| Jingguo Ren | 4 | 0 | 1.01 |
| Han Wang | 5 | 5 | 2.48 |